This study is funded by The Swedish National Graduate School in Mathematics, Science and Technology Education.
References
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30 Anna L. V. Lundberg
3
ATD and CoP in a framework for investigating social networks in physics classrooms
Jesper Bruun
Department of Science Education, University of Copenhagen Abstract. The article presents a tool for analysing transcribed and annotated video recordings. The tool relies on a network representation of the data, where the nodes derive from categories of activities. Following a summary of the observed learning situation, it is suggested how anthropological theory of the didactical (ATD) and communities of practice (CoP) can be incorporated in the network representation in order to investigate student discussion networks in physics classrooms.
Introduction
One of the major concerns for researchers in physics education is whether the students of a given class learn physics or not. Indeed, it is not clear what it means to have learned physics. Learning physics may consist of mastering different modes/forms of representation (Dolin, 2002), or it may amount to refining and organising conceptual structures to be retrieved as appropriate (diSessa, 1993). One view is that the cognitive development of the individual learner needs to be in focus when investigating science (and therefore physics) learning. A complementary view is that learning in general, and therefore the learning of physics, is the development of shared repertoire by a group over time (Wenger, 1998). However, what the dynamics of physics learning actually is seems to be an underdeveloped area.
One strategy for shedding light on how physics is learned is to observe learning situations in physics classes where the students engage in an appropriate assignment. The assignment - and the related tasks needed to complete it - may be designed or initiated by researchers or more naturally occurring (designed or initiated by
32 Jesper Bruun
teachers or even students) in the course of a typical physics class. The aim in either case is to make a detailed analysis of a particular learning situation, in order to identify the processes by which physics is learned.
One opportunity for achieving data for such analysis is to video record students participating in group discussions about a particular physics problem. The video recordings may serve as documentation for some of the processes going on in the learning situation, and they may be analysed qualitatively or as a mixture of qualitative and quantitative data (Johnson & Onwuegbuzie, 2004). With the proper use of qualitative methods and theory, such as thematic analysis (Braun & Clarke, 2006) and ATD/CoP, one should be able to identify categories consistent for the theory for a further quantitative treatment. In this paper, the quantitative treatment utilizes network theory as it is named in physics or graph theory as it is named in mathematics.
The anthropological theory of the didactic(al) (ATD) and communities of practice (CoP) are both theories aiming at understanding the activities of humans. ATD focuses on the strategies and justifications (praxeologies) for solving problems which can be abstracted from a non-individual oriented analysis of teaching, learning situations, and the materials used in them (Rodriguez et al., 2008, Artigue, 2006).
CoP on the other hand, as applied to an educational perspective, has four aspects, namely: participation/reification, designed/emergent, local/global, and negotiability/identification (Wenger, 1998), all pertaining to individuals or sets of individuals. Wenger denotes these pairs of concepts dualities, because they exist as two parts of a coin:
without participation from learners existing reifications become meaningless and on the other hand reifications such as (but not exclusively) teaching materials, are the basis for participation.
Some research (Shaffer et al., 2009) suggest that observational data from a framework resembling CoP, can be described with a graph theoretical approach where appropriate categories of action in the learning situation are recorded as well as the order in which they occur. In this paper, a notion of representing observational data is pursued with the ultimate aim of making relations, similarities, and differences between ATD and CoP explicit. This is a challenging task, since the two theories have different foci.
In this work, the video recorded activities of four Danish high school students, one male and three female, which serve to develop a
3. ATD and Communities of Practice 33 network representation. The network shows how the dynamics of a conversation about physics can be illustrated using a set of categories.
The “data” is a 400 second recording of the students engaging in a physics problem on predicting the ranking of currents at different places in an electrical circuit.
This particular situation has been selected from a larger data set (approximately 1 hour with different students), because it is suitable for a first attempt of describing a student discussion using networks, ATD, and CoP. First, the students actually engage in discussion with each other. Second, as will be shown, one student arguably changes her problem-solving strategy for a specific physics assignment, while three other students do not. Third, the technical quality of the material has enabled the researcher to clearly code the recording.
The focus in this paper is on describing learning situation as a network of categories. Also, this paper investigates the question of how physics praxeologies of ATD and shared repertoire of CoP are connected and may be captured by a network representation of the situation. Ultimately, the questions I wish to answer is, (1) what change in behaviour (utterances, gestures, actions) do the students display when about electrical current in a specific system for each of the participants and (2) what processes of communications are observable in the analysed data set?
Background
To learn science and in particular physics can be viewed as learning to work with different kinds of representation (Boulter & Buckley, 2000, Dolin, 2003). Dolin (2002) argues for seven distinct types of representation, namely the phenomenological, conceptual, mathematical-symbolic, mathematical-graphical, experimental, pictorial, and the kinaesthetic. To master a subject in physics is to master all the representations to some level given by the educational system.
It can be argued that at least some of the knowledge inherent in using these forms of representation is tacit. For example, an undergraduate student working with mechanics might not be aware that a specific conceptual schema is at work, when he explains how a moving object is affected by an applied force (diSessa, 1993). At some point however, the tacit knowledge in play in an observed teaching situation should be expressed by the learner in a way discernable to the observer, if this observer is to claim that learning has taken place.
Otherwise, claims of learning become just that: claims.
34 Jesper Bruun
However, one must acknowledge that there can be many signs of learning taking place or of a student possessing knowledge, which are not stated verbally or explicitly written down. Gestures may play an important role in student communication, as has been shown by Roth
& Lawless (2002). They found that students working with physics develop gestures which start out as actual depictions of the physical processes or objects, where the gesturing start before the actual words they utter, while they end up being short hand metaphoric versions of the same processes or objects, which are performed almost exactly at the same time as the words accompanying them. This also serves as an example that when learning, people change their behaviour in an observable way. Their actions change.
In order to quantify actions using a network approach [1], Shaffer et al. (2009) used a framework called the epistemic frame, claiming that a culture has a grammar composed of skills, knowledge, identity, values, and epistemology. These categories form the basis of a coding scheme, where if a subject in an activity seen from an observer’s perspective as belonging to the category skill then the activity is labelled accordingly. Thus, these categories can be named activity categories. This framework is reminiscent of the work of Wenger (1998) where a community of practice has a shared repertoire. One difference is that the framework of Shaffer et al. has been operationalised in their work, whereas Wenger does not operationalise his theory in a specific research design. Further similarities and differences are beyond the scope of this paper, and will not be pursued further. However, their translation of the framework into a time based network description can be helpful for the present work.
From their framework Shaffer et al. (2009) make a number of categories, and put their data in to these categories. Then they analyse data one time segment, δt, at a time. If two “activity categories” are performed within δt, then a non-directed link is drawn between the two. As time passes, some nodes become more connected than others resembling the fact that some types of action are performed more often than others. Looking at the whole network, as time passes may give information on what actions are tightly linked, and what actions are more isolated.
Transferring information about learner activities from the qualitative framework of epistemic frames to the quantitative network descriptions allows for mathematical analyses of the network, which can then be reinterpreted into the qualitative framework. This allows for an evidence based assessment of the learning situation rooted in
3. ATD and Communities of Practice 35 very direct way on a qualitative theory. In the case of Shaffer et al.
(2009), where they analyse the actions of persons playing a learning game called Urban Science (see Schaffer et al. (2009) for details), they hypothesise that learning progression can be connected to the structural properties of a developing network.
Shaffer et al.’s (2009) approach is interesting to this paper. They define relevant categories on the basis of a theory and code some research material (qualitative data), and transfer these codes to a mathematically rooted network representation (quantifying the data).
From the networks different structural properties of the activities are then extracted and re-interpreted in to the theory.
The theoretical frameworks used in this work are different, because they are not based on the assumptions of epistemic frames, but they also have their categories. In ATD categories describing learner activities should be discernable from relevant praxeologies (Tetchueng et al., 2008). Praxeologies consist of a theoretical block (justifications) and a practical block (the activities). The theoretical block is subdivided into a theory and technology section, while the practical block is divided into tasks and techniques (Rodriguez et al., 2008).
Students solving problems in physics as analysed by ATD requires the notion of a praxeology. To solve a problem requires the activation (or development) of an appropriate praxeology or set of praxeologies.
A problem can be decomposed into a set of tasks, each of which are dealt with by some techniques, each of which are again justified by a technology, which is a way of employing theory in practice (Tetchueng et al., 2008).
Tetchueng et al. (2008) made a learning management system for teacher education where they created predefined task-technique pairs for solving problems. The work relies on experts defining the correct task-technique pair, and learners acquiring them. In this work, I will go the other way around. From the data, praxeologies (task-technique-technology(-theory)), should be abstracted in order to see, what problem solving strategies the students subscribe to and why.
In ATD, the term “why” refers to the disciplinary justification for using a given technique (Chevallard 2006). So, if we ask why a student enacts a given technique, we are not expecting an answer based on the student’s social situation or how the student feels at that time. However, in CoP it would be a question of the shared repertoire in the community and the identity of the student (Wenger, 1998).
Thus, in CoP asking why also entails social and identity factors.
36 Jesper Bruun
From this it seems it seems likely that the praxeologies from ATD may fall into the shared repertoire of a community of practice, while the praxeological equipment (Rodriguez et al., 2008) of the student would be part of the students’ identity. Here, the praxeological equipment is interpreted as the praxeologies available for a student to enact in a given context.
However, this author believes that disciplinary praxeologies are not exhaustive when dealing with the dimensions of a learning situation (see Wenger, 1998, chapter 12) as seen from a CoP point of view.
This is because the CoP aspects of learning include more than the disciplinary aspect, for example student motivation and student-student relations. The following summary aims both at describing the disciplinary part of the students’ discussion, but with a focus on the individuals and at highlighting some of the student-student interaction.